Voice Recognition Systems: Unveiling Complexity, Mitigating Spoofing Risks, and Enhancing Security

This research project delves into the realm of voice recognition systems, leveraging peer-reviewed articles and scholarly journals to explore their mechanisms, spoofing techniques, and security considerations when integrated with Artificial Intelligence (AI). By synthesizing historical insights from expert-reviewed literature, the study aims to identify security weaknesses inherent in voice recognition systems and propose advancements in anti-spoofing technologies. Furthermore, the research explores authentication methods to mitigate risks posed by AI-driven voice impersonations, ultimately aiming to contribute to the development of robust safeguards against unlawful exploitation in voice recognition systems.

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Work Title Voice Recognition Systems: Unveiling Complexity, Mitigating Spoofing Risks, and Enhancing Security
Access
Open Access
Creators
  1. Jon Paolo Dimaculangan
Keyword
  1. Penn State Mont Alto Academic Festival 2024
  2. Undergraduate Research
License CC BY 4.0 (Attribution)
Work Type Poster
Acknowledgments
  1. Faculty Mentor: Elizabeth Denlea
Publication Date April 19, 2024
Related URLs
  1. https://montalto.psu.edu/academics/festival
Deposited April 11, 2024

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Version 1
published

  • Created

    April 11, 2024 14:31 by tlr15

  • Updated

    April 11, 2024 14:31 by [unknown user]

  • Updated Keyword, Related URLs, Description, and 1 more Show Changes

    April 11, 2024 14:32 by tlr15

    Keyword
    • Penn State Mont Alto Academic Festival 2024, Undergraduate Research
    Related URLs
    • https://montalto.psu.edu/academics/festival
    Description
    • This research project delves into the realm of voice recognition systems, leveraging peer-reviewed articles and scholarly journals to explore their mechanisms, spoofing techniques, and security considerations when integrated with Artificial Intelligence (AI). By synthesizing historical insights from expert-reviewed literature, the study aims to identify security weaknesses inherent in voice recognition systems and propose advancements in anti-spoofing technologies. Furthermore, the research explores authentication methods to mitigate risks posed by AI-driven voice impersonations, ultimately aiming to contribute to the development of robust safeguards against unlawful exploitation in voice recognition systems.
    Publication Date
    • 2024-04-19
  • Updated Acknowledgments Show Changes

    April 11, 2024 14:32 by tlr15

    Acknowledgments
    • Faculty Mentor: Elizabeth Denlea
  • Added Creator Jon Paolo Dimaculangan

    April 11, 2024 14:32 by tlr15

  • Added Voice Recognition Systems.pdf

    April 11, 2024 15:29 by tlr15

  • Updated License Show Changes

    April 11, 2024 15:29 by tlr15

    License
    • https://creativecommons.org/licenses/by/4.0/
  • Published

    April 11, 2024 15:29 by tlr15

  • Updated

    April 11, 2024 22:03 by [unknown user]